Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
A primal-dual algorithm for minimizing a sum of Euclidean norms
Journal of Computational and Applied Mathematics
An Efficient Primal-Dual Interior-Point Method for Minimizing a Sum of Euclidean Norms
SIAM Journal on Scientific Computing
An Efficient Algorithm for Minimizing a Sum of Euclidean Norms with Applications
SIAM Journal on Optimization
An Efficient Algorithm for Minimizing a Sum of p-Norms
SIAM Journal on Optimization
Improvements of some projection methods for monotone nonlinear variational inequalities
Journal of Optimization Theory and Applications
Comparison of Two Kinds of Prediction-Correction Methods for Monotone Variational Inequalities
Computational Optimization and Applications
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This paper presents a variational inequality (VI) approach to the problem of minimizing a sum of p-norms. First the original problem is reformulated as an equivalent linear VI. Then an improved extra-gradient method is presented to solve the linear VI. Applications to the problem of p-norm Steiner Minimum Trees (SMT) shows that the proposed method is effective. Comparison with the general extra-gradient method is also provided to show the improvements of the new method.